In general, the present disclosure is directed to a time of flight (ToF) sensor arrangement that may be utilized by a robot (e.g., a robot vacuum) to identify and detect objects in a surrounding environment for mapping and localization purposes. In an embodiment, a robot is disclosed that includes a plurality of ToF sensors disposed about a housing of the robot. Two or more ToF sensors may be angled/aligned to establish overlapping field of views to form redundant detection regions around the robot. Objects that appear therein may then be detected by the robot and utilized to positively identify, e.g., with a high degree of confidence, the presence of the object. The identified objects may then be utilized as data points by the robot to build/update a map. The identified objects may also be utilized during pose routines that allow the robot to orient itself within the map.
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2. The robotic surface cleaning device of claim 1, wherein the first and second ToF sensors are infrared-type ToF sensors.
The invention relates to a robotic surface cleaning device equipped with time-of-flight (ToF) sensors for improved navigation and obstacle detection. The device addresses the challenge of accurately mapping and navigating environments while avoiding obstacles, particularly in low-light or dynamic conditions. The robotic cleaning device includes at least two ToF sensors, which are infrared-type sensors, to measure distances to objects by emitting infrared light pulses and calculating the time it takes for the light to reflect back. These sensors enhance the device's ability to detect and avoid obstacles, as well as create precise maps of the cleaning area. The use of infrared-type ToF sensors ensures reliable performance in varying lighting conditions, as they are less affected by ambient light compared to visible-light sensors. The device may also include additional features such as a cleaning mechanism, a power source, and a control system to manage sensor data and navigation. The integration of infrared ToF sensors improves the device's efficiency and safety, allowing it to operate autonomously in complex environments.
3. The robotic surface cleaning device of claim 1, wherein each ToF sensor of the first plurality of ToF sensors is vertically offset relative to a corresponding ToF sensor of the second plurality of ToF sensors.
A robotic surface cleaning device includes multiple time-of-flight (ToF) sensors arranged in two distinct groups. The first group of ToF sensors is vertically offset relative to the second group, creating a staggered configuration. This arrangement improves depth perception and obstacle detection by providing multiple vertical measurement points. The device uses these sensors to map and navigate environments, avoiding collisions and efficiently cleaning surfaces. The vertical offset enhances accuracy in detecting objects at different heights, such as low obstacles or elevated surfaces, ensuring comprehensive coverage during cleaning operations. The sensors work in conjunction with other components, such as a controller and a cleaning mechanism, to autonomously operate the device. The staggered sensor layout reduces blind spots and improves spatial awareness, making the device more reliable in dynamic environments. This design is particularly useful for robotic vacuum cleaners or mops that require precise navigation and obstacle avoidance.
4. The robotic surface cleaning device of claim 1, wherein the first and second ToF sensors are arranged in a first staggered configuration such that a first imaginary line drawn substantially transverse from a surface to be cleaned intersects with the first ToF sensor does not intersect with the second ToF sensor.
A robotic surface cleaning device is designed to autonomously navigate and clean floors while avoiding obstacles. The device includes multiple time-of-flight (ToF) sensors for detecting objects and measuring distances. The invention addresses the challenge of accurately sensing the environment in a compact form factor, particularly when sensors may be obstructed or misaligned. The device features first and second ToF sensors arranged in a staggered configuration. This arrangement ensures that an imaginary line drawn perpendicular to the surface being cleaned intersects with the first sensor but not the second. This staggered placement improves spatial coverage and reduces blind spots, allowing the device to detect obstacles more reliably. The sensors work together to provide a comprehensive view of the surrounding area, enhancing navigation and cleaning efficiency. The staggered design also minimizes interference between sensors, ensuring accurate distance measurements. This configuration is particularly useful in tight spaces or when cleaning near walls and furniture, where precise obstacle detection is critical. The overall system enables the robotic device to operate autonomously with improved accuracy and safety.
5. The robotic surface cleaning device of claim 1, wherein navigation controller is further to calculate a height of the object relative to the robotic cleaning device based, at least in part, on the geometry of the first redundant detection region and the relative distance between the robotic cleaning device and the object.
A robotic surface cleaning device is designed to autonomously navigate and clean surfaces while avoiding obstacles. The device includes a navigation controller that uses sensor data to detect and map the environment. The navigation controller calculates the height of an object relative to the device by analyzing the geometry of a redundant detection region—a region where multiple sensors overlap to ensure accurate detection—and the relative distance between the device and the object. This height calculation helps the device determine whether the object is an obstacle that needs to be avoided or a surface feature that can be cleaned. The redundant detection region improves reliability by cross-verifying sensor data, reducing false positives and ensuring precise navigation. The device may also include additional features such as obstacle avoidance, path planning, and cleaning mechanisms like brushes or suction systems. The height calculation is particularly useful in environments with varying surface levels, such as carpets, rugs, or furniture, allowing the device to adapt its cleaning strategy accordingly. The system enhances the device's ability to operate efficiently and safely in dynamic environments.
6. The robotic surface cleaning device of claim 1, wherein navigation controller uses the first and second ToF sensors during a pose routine to determine an orientation of the robotic surface cleaning device in a map stored in a memory of the robotic surface cleaning device.
A robotic surface cleaning device includes a navigation controller that uses time-of-flight (ToF) sensors to determine the device's orientation within a stored map. The device is designed for autonomous navigation and cleaning of surfaces, addressing challenges in accurately tracking position and orientation in dynamic environments. The navigation controller employs at least two ToF sensors to measure distances to surrounding objects, enabling the device to calculate its orientation relative to the stored map. This process involves comparing sensor data with the map to align the device's current position and orientation with the mapped environment. The ToF sensors provide real-time depth information, allowing the device to adjust its path and avoid obstacles while maintaining accurate navigation. The stored map may include pre-mapped layouts of indoor spaces, such as rooms or corridors, and the device updates its position within this map using the ToF sensor data. This method improves navigation accuracy, reducing errors caused by sensor noise or environmental changes. The device may also use additional sensors, such as cameras or inertial measurement units, to supplement the ToF data for enhanced precision. The overall system enables the robotic cleaner to navigate efficiently and autonomously, adapting to its surroundings while performing cleaning tasks.
8. The robotic surface cleaning device of claim 7, wherein at least one ToF sensor of the second plurality of ToF sensors has a detection region that at least partially overlaps with the detection region of the first and/or second ToF sensor to provide a third redundant detection region, and wherein the controller is further to calculate a height of the object based on the object being detected in the third redundant detection region.
A robotic surface cleaning device is designed to autonomously navigate and clean surfaces while avoiding obstacles. The device includes a first time-of-flight (ToF) sensor and a second ToF sensor, each with distinct detection regions, to detect objects in the device's path. The device also includes a second plurality of ToF sensors, at least one of which has a detection region that overlaps with the detection regions of the first and/or second ToF sensors, creating a third redundant detection region. This overlapping detection region enhances object detection accuracy by providing multiple sensor inputs for the same area. The device's controller processes data from these sensors to calculate the height of detected objects, improving obstacle detection and navigation. The redundant detection regions ensure reliable object detection even in challenging environments, such as low-light conditions or cluttered spaces, by cross-referencing data from multiple sensors. This redundancy reduces false positives and enhances the device's ability to navigate safely and efficiently. The system is particularly useful in autonomous cleaning applications where precise obstacle detection and avoidance are critical.
10. The computer-implemented method of claim 9, further comprising calculating, by the controller, a height of an object detected within the second redundant detection region.
This invention relates to a computer-implemented method for detecting and analyzing objects within a detection region using redundant sensors. The method addresses the challenge of accurately identifying and measuring objects in environments where sensor data may be incomplete or unreliable due to obstructions, interference, or sensor limitations. The system employs multiple sensors to create overlapping detection regions, ensuring that objects are detected even if one sensor fails or is obstructed. The method involves processing sensor data to identify objects within a primary detection region and then verifying their presence in a secondary, redundant detection region. This redundancy improves detection reliability. Additionally, the method calculates the height of detected objects within the redundant detection region, providing further dimensional analysis. The system may also adjust sensor parameters, such as field of view or sensitivity, based on environmental conditions or object characteristics to optimize detection accuracy. The method is particularly useful in applications like autonomous navigation, industrial automation, and security monitoring, where reliable object detection is critical. By combining redundant sensor data and height measurement, the invention enhances object detection robustness and precision.
11. The computer-implemented method of claim 9, further comprising executing, by the controller, a pose routine that orients the robotic surface cleaning device within a map stored in a memory.
This invention relates to robotic surface cleaning devices and methods for improving their navigation and cleaning efficiency. The problem addressed is the need for robotic cleaners to accurately determine their position and orientation within an environment to avoid missed cleaning areas and collisions. The method involves using a controller to execute a pose routine that orients the robotic device within a stored map. The map is generated by the device as it moves through the environment, using sensor data to detect obstacles and boundaries. The pose routine adjusts the device's position and orientation based on the map, ensuring it follows an optimal cleaning path. The device may also use simultaneous localization and mapping (SLAM) techniques to update the map in real-time. The method further includes adjusting the device's movement speed and direction to avoid obstacles and maintain efficient coverage. The controller may also analyze the map to identify high-traffic areas or frequently missed spots, prioritizing cleaning in those regions. The invention improves cleaning efficiency by ensuring the device covers the entire area while avoiding unnecessary movements or collisions.
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April 3, 2019
December 13, 2022
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